AI ERP with agents inside the systems you run
AI phone and voice agents for real calls
LLM.coPrivate, self-hosted LLM deployments
Legal AI infrastructure for firms
AI RFP discovery and response drafting
Automatic.coBusiness process automation
CyberAttack.aiThreat detection and defense
Secure AI virtual data rooms
12+
Years building software
Founded 2013
390+
Projects shipped
Web, mobile, SaaS, AI
22
Disciplines in house
No subcontracted seams
100%
Code ownership to you
From the first commit
What you are buying
What software development services actually cover
The phrase covers four distinct kinds of work that get sold as one thing. Knowing which you need changes who you should hire and what you should pay.
Product development
Building software that does not exist yet — a first release, a new module, a replacement for a system that has outgrown itself. This is the bulk of what most companies mean by custom software development services, and it is the work where scope discipline matters most, because everything is negotiable until it is built.
Integration and platform work
Making systems you already own agree with each other: APIs, webhook infrastructure, data pipelines, identity. Rarely glamorous, frequently the highest-return engineering a company can buy, and almost always underestimated because the difficulty lives in other people's data rather than in your own code.
Modernization
Moving off a stack that still works but is becoming expensive to staff, secure or extend. Done well it is incremental — route by route, table by table, with the old system serving customers throughout. Done as a rewrite it is the single most common way a software budget disappears.
Capacity
Engineers added to a team you already have, for a launch, a migration, or a skill you need for six months and not forever. The deliverable is throughput rather than a product, and it is priced and managed differently from everything above.
The catalogue
Every discipline a production system needs
Most projects need several of these at once. Buying them from one team is not a convenience argument — it is what stops a design being approved that engineering cannot build, or a test suite arriving after the architecture is already fixed.
Build
Net-new software, from a first release to a platform that carries the business.
Custom Software Development
Line-of-business systems modeled on the way your company actually runs, including the exceptions people currently handle by hand.
Web Application Development
React, Next.js, Rails and Django applications, server-rendered where it matters for speed and search visibility.
Mobile App Development
Native iOS and Android, or a single React Native codebase when the roadmap does not justify maintaining two.
SaaS Product Development
Multi-tenant architecture, billing, roles and usage metering built in from the first sprint rather than retrofitted later.
MVP Development
A narrow, genuinely usable first release in six to ten weeks — enough product to put in front of real users.
Enterprise Software
SSO, granular permissions, audit trails and the documentation a procurement and security review will ask for.
Connect and operate
The work that decides whether software survives contact with production.
API Development & Integration
REST and GraphQL APIs, webhook infrastructure, and the integration work that makes two systems agree on one version of the truth.
Cloud & DevOps Engineering
AWS, GCP and Azure environments defined in Terraform, with CI/CD, staged rollouts and alerting that reaches a human.
QA & Software Testing
Automated unit, integration and end-to-end suites plus load and regression testing, so a release stops being a gamble.
Legacy Modernization
Incremental migrations off aging stacks, route by route and table by table, while the old system keeps serving customers.
Cybersecurity Engineering
Hardening, dependency and access audits, and remediation work scoped against real findings rather than a checklist.
Data Engineering
Pipelines, warehouses and reporting layers that make the numbers in two systems stop disagreeing.
Design and teams
Deciding what to build, and staffing the people who build it.
UI/UX Design
Interfaces drawn against the real data model, so what gets approved in design is something engineering can actually build.
Prototyping & Discovery
A clickable prototype and a written scope before the budget is committed, so the expensive decisions are made cheaply.
Technology Architecture
The decisions that are expensive to reverse — data model, service boundaries, tenancy, hosting — made once and documented.
Staff Augmentation
Senior engineers embedded in your team, your sprints and your repository, with a defined ramp-off rather than an open invoice.
Dedicated Dev Teams
A standing pod — engineers, a lead, QA and design as needed — working your backlog under one contract.
Project Management
Delivery you can audit: written acceptance criteria, two-week increments, and a working build at the end of each.
White-Label Development
Engineering delivered under an agency's brand, invisible to their client — a large share of what we do and, until now, almost impossible to find from here.
AI engineering
AI wired into the systems you already run, with a way to prove it works.
AI Application Development
Full-stack AI products, evaluated against a fixed test set rather than shipped on a convincing demo.
AI Agent Development
Multi-step agents with tool access, guardrails and an audit trail of what they did and why.
Private LLM Deployment
Self-hosted Llama, Mistral and Qwen for data that cannot leave your perimeter.
RAG & Document Intelligence
Cited answers over your own documents, with extraction pipelines for the formats nobody wants to parse by hand.
Engagement models
Three ways to buy the same team
The right structure depends on whether your scope is fixed, your roadmap is continuous, or your own team just needs depth for a stretch. All three are month-to-month with no exit penalty, and we will tell you when the cheapest of them is the right answer.
Fixed-scope build
Fixed price, fixed date
Defined product, defined budget
You know what needs building. We scope it in discovery, quote a fixed price against that scope, and deliver on a published timeline. Change requests are priced individually rather than absorbed silently.
- Written acceptance criteria
- Discovery credited to the build
- Two-week increments
- Code and infrastructure yours at launch
Dedicated pod
Monthly, cancel anytime
Continuous roadmap, shifting priorities
A standing team working your backlog in your tools. Capacity is fixed, direction is yours, and you can resize or stop at the end of any month.
- Same people every sprint
- US-hours overlap
- Your repo, your board
- 30-day notice, no penalty
Embedded engineers
A defined stretch
In-house team that needs depth
Senior specialists dropped into your existing team for a migration, a launch crunch, or a skill the team does not have and does not need permanently.
- Individually interviewed
- Ramps in under two weeks
- Your process, not ours
- Defined ramp-off
What it costs
Software development pricing, without the discovery call
Real ranges for the engagements we actually run. Every firm's numbers differ; what should not differ is being told them before you have spent an hour on a call.
| Engagement | Typical range | Timeline | What it buys |
|---|---|---|---|
| Prototype or discovery | Scoped per engagement | 2 – 4 weeks | Clickable prototype, architecture diagram, risk list and a costed scope. Yours to take elsewhere. |
| MVP | Scoped per engagement | 6 – 10 weeks | A narrow first release real users can use — one workflow done properly rather than five done partially. |
| Full product build | Scoped per engagement | 3 – 9 months | Multi-role application with integrations, admin tooling, test coverage and production infrastructure. |
| Dedicated pod | Scoped per engagement | Monthly | A standing team on your backlog. Cancel at the end of any month, no exit penalty. |
| Embedded engineers | Scoped per engagement | Defined stretch | Senior specialists inside your team and your process, with a planned ramp-off. |
Ranges assume US-based senior engineers and include QA, DevOps and project management rather than quoting them separately. A quote below these bands usually means one of those three was left out of the scope.
Choosing a partner
How to evaluate a software development services company
Six questions that separate firms quickly. We have written the answer we would give to each, so you can hold us to the same standard as everyone else you are talking to.
Who actually writes the code?
Ask whether the engineers in the pitch are the engineers on the project, and whether any work is subcontracted. Ours are in house across all 22 disciplines, which is the reason we can say no seams and mean it.
What happens to the code if we stop?
Source, infrastructure-as-code, CI configuration and documentation should transfer on request at any point, not at some milestone. If a framework or hosting arrangement makes leaving expensive, that is a commercial decision dressed as a technical one.
How is AI-written code reviewed?
Most firms now ship AI-assisted code, including us — the speed is real. The question is what gates it. Every pull request here has a human reviewer with authority to reject, and automated checks gate the merge without replacing that judgment.
What does a bad week look like?
A vendor who cannot describe one has not had enough projects. Ask how a missed estimate gets communicated, and how quickly. Two-week increments with a working build exist precisely so a slip is visible in fourteen days rather than at the end.
Is discovery credited against the build?
It should be, and it should produce a document you keep regardless. Discovery sold as a non-refundable gate on a larger contract is a sales mechanism.
Who owns the relationship day to day?
Routing every technical question through an account manager adds a day to each answer. Engagements here give you direct access to the engineering lead on your project.
The full checklist — ownership, testing, security, AI use, and how to leave — is in our guide on choosing a software development company.
How an engagement runs
Twelve weeks you can audit
Software projects fail quietly, in the gap between a status report and reality. Every two weeks there is a working build on a URL you can click, which is what keeps that gap from opening.
Engineering standards
What every service has in common
Whichever discipline you buy, the path to production is the same. AI writes a great deal of the code we ship — that is a speed advantage we use deliberately, and it is exactly why nothing merges on confidence alone.
Typed end to end
Typed contracts at every service boundary. A schema change that breaks a caller fails in CI, not in support.
Reviewed by a person
Every pull request has a human reviewer who can reject it. Automated checks gate the merge; they do not replace judgment.
Observable on day one
Structured logs, traces and alerts ship with the first release, so the first production incident is diagnosable.
Handed over, not held
Repository, infrastructure and documentation transfer to you at launch. Nothing is locked behind a proprietary framework.
Questions
Buying software development services
What prospective clients ask before a first call.
Full-cycle: discovery and product strategy, UI and UX design, web and mobile application development, SaaS and enterprise platforms, API and integration work, cloud and DevOps engineering, QA and testing, security, data engineering, and AI development.
The reason to buy them together is that the seams between disciplines are where outsourced projects usually fail. A design approved without reference to the data model, or a build handed to a separate QA vendor, creates a gap that somebody has to pay to close later.
Yes. A single discipline is a normal engagement — a security remediation, a mobile launch, a test suite for a codebase that never had one, or a migration off a framework nobody on your team still knows.
Embedded engagements exist precisely for this. Our engineers work inside your team and your process for a defined stretch, reporting to your engineering lead rather than routing through an account manager.
By asking who maintains the system after we leave. A stack your team already knows is worth more than a marginally better one they will have to learn under pressure, and we will say so even when it means recommending something less interesting to build.
Where there is no in-house team to inherit it, we choose for operational boredom: mature frameworks, managed databases, and infrastructure defined in code so it can be rebuilt from scratch.
Two-week increments, each ending with working software on a preview URL you can click. You review the product rather than a status deck, and priorities can change between increments.
Discovery comes first and produces an architecture diagram, a risk list and an estimate. That document is yours whether or not you continue — you can take it to another firm if you would rather.
Frequently, and it is usually the better arrangement when the in-house team is strong but missing specific depth. Our engineers join your repository, your sprint cadence and your standups.
The alternative — a sealed-off vendor team delivering over the wall — tends to produce software your own engineers are reluctant to own afterward.
You take everything: source code, infrastructure defined in Terraform under your own cloud account, CI configuration, and documentation written for the engineer who inherits it.
Some clients keep a support SLA for monitoring, patching and dependency upgrades. Others keep a smaller pod running continuous iteration. Neither is a condition of the first engagement.
Discovery is the smallest engagement, an MVP the next step up, and a full product build the largest. A dedicated pod is bought monthly rather than as a project. The table above sets out each shape.
The variable that moves a quote most is not features, it is integrations — the number of systems your software has to agree with, and how well those systems are documented.
Off-the-shelf wins whenever your process is genuinely standard: accounting, payroll, CRM in its plain form. Custom earns its cost when the process is the business — the workflow nobody else runs, the exceptions your staff currently handle by hand, the integration no vendor has built.
The honest test is whether you are about to pay to make a packaged product behave like something it is not. Configuration and middleware to force that fit often costs more than building the thing.
Discovery is two to four weeks. An MVP is six to ten. A full build is three to nine months depending on integration count and how many teams have to approve decisions.
What actually sets the pace after engineering is your side: how quickly feedback comes back on each two-week increment, and how fast security or procurement reviews clear.